Machine learning-assisted optimization of TBBPA-bis-(2,3-dibromopropyl ether) extraction process from ABS polymer

Yan Wan; Qiang Zeng; Pujiang Shi; Yong-Jin Yoon; Chor Yong Tay; Jong-Min Lee

doi:10.1016/j.chemosphere.2021.132128

Machine learning-assisted optimization of TBBPA-bis-(2,3-dibromopropyl ether) extraction process from ABS polymer

Chemosphere. 2022 Jan;287(Pt 2):132128. doi: 10.1016/j.chemosphere.2021.132128. Epub 2021 Sep 2.

Authors

Yan Wan¹, Qiang Zeng¹, Pujiang Shi², Yong-Jin Yoon³, Chor Yong Tay⁴, Jong-Min Lee⁵

Affiliations

¹ Energy Research Institute, Nangyang Technological University, 1 Cleantech Loop, 637141, Singapore; School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, 637459, Singapore.
² Energy Research Institute, Nangyang Technological University, 1 Cleantech Loop, 637141, Singapore.
³ Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
⁴ Energy Research Institute, Nangyang Technological University, 1 Cleantech Loop, 637141, Singapore; School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore; School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore.
⁵ Energy Research Institute, Nangyang Technological University, 1 Cleantech Loop, 637141, Singapore; School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, 637459, Singapore. Electronic address: jmlee@ntu.edu.sg.

PMID: 34509015
DOI: 10.1016/j.chemosphere.2021.132128

Abstract

The increasing amount of e-waste plastics needs to be disposed of properly, and removing the brominated flame retardants contained in them can effectively reduce their negative impact on the environment. In the present work, TBBPA-bis-(2,3-dibromopropyl ether) (TBBPA-DBP), a novel brominated flame retardant, was extracted by ultrasonic-assisted solvothermal extraction process. Response Surface Methodology (RSM) achieved by machine learning (support vector regression, SVR) was employed to estimate the optimum extraction conditions (extraction time, extraction temperature, liquid to solid ratio) in methanol or ethanol solvent. The predicted optimum conditions of TBBPA-DBP were 96 min, 131 mL g^-1, 65 °C, in MeOH, and 120 min, 152 mL g^-1, 67 °C in EtOH. And the validity of predicted conditions was verified.

Keywords: Brominated flame retardant; Extraction; Machine learning; Response surface methodology; e-waste plastic.

MeSH terms

Ether*
Ethers
Flame Retardants*
Machine Learning
Polymers

Substances

Ethers
Flame Retardants
Polymers
Ether